Role of the Krebs Cycle Metabolites in Retinal Angiogenesis
Bibliographic record
Abstract
Purpose Retinopathy of prematurity (ROP), a major cause of blindness in developed countries, occurs in two phases : the cessation of normal eye development after birth and a subsequent abnormal and exaggerated vessel growth. Peripheral hypoxia occur after the first phase in premature eye and induce production of many growth factors implicated in this second destructive neovascularization phase. Our laboratory has previously demonstrated the role of succinate/GPR91 in the modulation of retinal vessel growth. Here, we investigated the role of α‐ketoglutarate (α‐KG) and its cognate receptor GPR99 in retinal angiogenesis. Methods Effects of α‐KG on developmental retinal vascularization were assessed following intravitreal injection of Sprague‐Dawley rat pups in development. Moreover, the effects of a siGPR99 knockdown following intravitreal injection were investigated in the neovascular phase of ROP. Endogenous expression of retinal GPR99 was examined in Sprague‐Dawley rat retinas by immunohistochemistry. In vitro, we investigated the expression of GPR99 and pro‐angiogenic factors by Western blot and PCR analysis. The ability of α‐KG to promote vessel sprouting was determined by aortic rings cultured. Results α‐KG significantly enhanced developmental vascular densities at different time points. Neovascularization was blocked by a siGPR99 and allowed normal vessel growth in ROP. Moreover, GPR99 was robustly expressed in RGCs as confirmed by co‐labeling with neuron markers and, in vitro, mainly in neuronal cells. Conditioned media from α‐KG stimulated‐neurons induced aortic rings sprouting, in correlation with an up‐regulation of pro‐angiogenic factors expression. Conclusions Our results disclose a pro‐angiogenic role for α‐KG and its receptor GPR99, providing additional supports for the involvement of metabolite signalling in ischemic conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".